For the modelling of novel solvent systemsfor CO2-capture in AspenPlus®, data fitting of physical-chemical properties is needed. In this work the challenges and results are presented for fitting such experimental data for aqueous solutions of 2-(diethylamino) ethanol (DEEA) and 3-(methylamino)propylamine (MAPA). Without CO2 present, the default regression tool of AspenPlus® gave good data fits for the binary systems H2O-MAPA and H2O-DEEA. In the presence of CO2, regression of parameters was not successful and an additional Particle Swarm Optimization (PSO) algorithm was needed to determine the many molecule-ion parameters for the ELECNRTL model. With this, for DEEA a good fit to experimental data has been obtained, whereas for MAPA, due to the high number of ionic species, the results were still not satisfactory. To resolve this, independent measurement of equilibrium constants for the ionic equilibria is recommended.